Wireless communication devices, such as mobile devices and base stations, typically include transmitter and receiver circuits (i.e., transceivers) in which power amplifiers are used to amplify a signal before wireless transmission to another device. However, some radio frequency (RF) power amplifiers generate out-of-band spurious emissions or otherwise add non-linear distortion to the amplified signal, where the distortion may include, for example, variations in phase differences or variations in amplitude differences. Significant distortion may result in poor signal quality.
Traditional approaches for meeting the out-of-band spurious transmission requirements would operate the power amplifier well below its maximum output power, or require very expensive and inefficient power amplifiers which are designed according to the maximum peak power that they have to handle. In order to reduce the cost and improve efficiency of the power amplifier, digital pre-distortion (DPD) systems have been developed to compensate for the intrinsic distortion characteristics of non-linear power amplifier devices. A traditional DPD system determines an error signal which reflects differences between an input signal and a feedback signal from the system output, and then, uses the error signal to determine a complementary distortion or inverse gain signal which is combined with the input signal to produce a pre-distorted signal that is input to, the power amplifier device. In many cases, this process results in effective cancellation of the distortion (i.e., the non-linearities) produced within the system, and a more linear output signal may result.
One approach for performing digital pre-distortion uses a polynomial model of the power amplifier that is evaluated to generate a pre-distortion function that is applied at the amplifier input to obtain a linear gain output. Other pre-distortion processes use one or more polynomials to adjust the input signal prior to amplification in order linearize the amplifier gain. In any case, the real-time processing requirements for evaluating a polynomial can impose significant complexity and processing costs in terms of the significant digital processing resources required to evaluate the polynomial.